IIT Kharagpur and Absolute joined the Quad cohort to develop a soybean field intelligence system called Smart Scout. This AI-enabled project helps farmers identify crop damage and lodging risks early. A media statement said, "Smart Scout uses cameras and AI to give farmers a clearer view of their crop."
Absolute, an AI-native bio-solutions company, and the Indian Institute of Technology Kharagpur (IIT Kharagpur) have been selected to develop Smart Scout, one of six projects in the inaugural cohort of the Quad’ Advancing Innovations for Empowering NextGen Agriculture (AI-ENGAGE) initiative.
IIT Kharagpur leads the Indian research team, with Absolute as its industry partner. Conceived as an advanced AI-enabled computer-vision system for soybean monitoring, Smart Scout is designed to strengthen field intelligence by enabling earlier identification of lodging risk and more precise assessment of crop damage.
Each AI-ENGAGE project draws researchers from at least three member nations, while Smart Scout involves all four. The cohort as a whole is supported by a combined Quad investment exceeding $6 million, with each agency funding its own country’s researchers. ICAR supports the Indian component of Smart Scout.
Lost yield, poor grain
A media statement said that lodging in soybean strikes late in the season, when pods are filling and plants are at their heaviest. (Lodging is when crop plants bend or fall over before harvest.)
Heavy rain softens the soil around the roots, strong wind pushes the plants over, and crops sown too densely grow tall, thin stems that give way easily. Insects that bore into the stem weaken plants further from the inside.
For a farmer, a lodged field means lost yield and poorer grain. Plants lying on wet soil are more prone to disease and pod rot, which lowers seed quality and the price it fetches. Flattened crops are also slow and wasteful to harvest, whether manually or by combine.
Now most farmers judge the extent of the damage by walking their fields plant by plant, often after the window for action has closed.
Smart scout
Smart Scout uses cameras and AI to give farmers a clearer view of their crop through the season. The system can be carried by hand or mounted on sprayers and other farm machinery, so scouting fits into work farmers already do.
The statement said it is being built to support three decisions every soybean farmer faces: where to look closer, how much has been lost, and when to harvest.
For crop monitoring, regular field images capture plant height, stand density, early signs of leaning and pest pressure, so emerging problems show up field by field while there is still time to respond.
For damage assessment, the system calculates a lodging score and the percentage of the field affected, and maps where the damage sits, giving farmers and agronomists a consistent, documented record of what was lost.
For harvest planning, Smart Scout estimates yield during the season by counting pods and measuring pod length, helping farmers decide which fields to harvest first and plan labour, machinery and sales.
Ajay Sharda of Kansas State University, USA, leads Smart Scout internationally as the project’s Lead Principal Investigator. In India, Peeyush Soni of IIT Kharagpur’s Department of Agricultural and Food Engineering serves as Principal Investigator, while Shivam Sharma from Absolute serves as Co-Principal Investigator.
The wider consortium also includes scientists from Kobe University in Japan and the University of Southern Queensland in Australia.
IIT Kharagpur leads the data and modelling foundations. Its team standardises how field images are captured, annotated and augmented, develops and refines the yield estimation models, and builds detection models that measure pest infestation in commercial fields and soybean nurseries. It also leads app development.
Absolute leads the components that turn those models into decisions in the field. It is developing the compact, AI-enabled computer vision system for real-time crop monitoring, the lodging score and percentage that inform crop planning, and in-season yield estimates drawn from pod length and count.
Absolute also leads the Smart Scout application and a data visualisation dashboard for validating the models, and it will evaluate how usable and accurate the system is in the field.
Smart Scout is a three-year project. Pilot trials in India will cover more than 30 acres of soybean across Madhya Pradesh, Maharashtra and Karnataka. Once validated, the work moves to farmer training, stakeholder workshops and knowledge sharing with the Quad partners.
Peeyush Soni said: “By bringing together IIT Kharagpur’s Agricultural and Food Engineering Department, Absolute and our Quad partners in the US, Japan and Australia, we aim to deliver field-ready AI that works under Indian conditions and can scale to millions of soybean hectares.”
Shivam Sharma said this is a significant moment for Absolute and for the evolution of agricultural innovation in India.
“In India’s soybean belt, one late monsoon storm during pod filling can flatten a crop and cost up to a third of its yield. Smart Scout is built to read that risk while it is still forming. With soybean a major focus of the Government’s National Mission on Edible Oils - Oilseeds, we see our work as closely aligned with that mission, helping farmers protect more of the crop they have already grown. Through this Quad collaboration, our field validation on smallholder farms will carry that intelligence from scientific research to better decisions on the farm,” Sharma said.